Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-02-24
2024-01-04
2023-11-02
Abstract—Reducing time in the machining process is important in order to increase the efficiency of the process. In this present study, a non-conventional method was used to minimise the tool path length in the drilling process in order to decrease machining time. Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) were applied to optimise the tool path in the drilling process. Then, the optimum tool path length was compared to the Genetic Algorithm and conventional methods. A workpiece with 158 holes was developed in Solidworks software in order to minimise the tool path length based on the drilling process. Then, the model was exported to Mastercam software for the simulation of tool path. The result of ACO and PSO showed that the optimisation process could reduce the tool path length in the drilling process as compared to the tool path length produced by Mastercam. It could be summarised that the simulation of non-conventional method is capable to determine the shortest tool path length, thus reducing machining time for the drilling process
